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Early Diagnosis

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Prediction models for early diagnosis of actinomycotic osteomyelitis of the jaw using machine learning techniques: a preliminary study.

BMC oral health
BACKGROUND: This study aimed to develop and validate five machine learning models designed to predict actinomycotic osteomyelitis of the jaw. Furthermore, this study determined the relative importance of the predictive variables for actinomycotic ost...

Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal irregularities in the electrical performance of the atria, and may cause heart thrombosis, stroke, arterial disease, thromboembolism, and heart failure...

Artificial intelligence assessment for early detection and prediction of renal impairment using electrocardiography.

International urology and nephrology
PURPOSE: Although renal failure is a major healthcare burden globally and the cornerstone for preventing its irreversible progression is an early diagnosis, an adequate and noninvasive tool to screen renal impairment (RI) reliably and economically do...

Deep Supervised Domain Adaptation for Pneumonia Diagnosis From Chest X-Ray Images.

IEEE journal of biomedical and health informatics
Pneumonia is one of the most common treatable causes of death, and early diagnosis allows for early intervention. Automated diagnosis of pneumonia can therefore improve outcomes. However, it is challenging to develop high-performance deep learning mo...

The application research of AI image recognition and processing technology in the early diagnosis of the COVID-19.

BMC medical imaging
BACKGROUND: This study intends to establish a combined prediction model that integrates the clinical symptoms,the lung lesion volume, and the radiomics features of patients with COVID-19, resulting in a new model to predict the severity of COVID-19.

Multiple instance learning detects peripheral arterial disease from high-resolution color fundus photography.

Scientific reports
Peripheral arterial disease (PAD) is caused by atherosclerosis and is a common disease of the elderly leading to excess morbidity and mortality. Early PAD diagnosis is important, as the only available causal therapy is addressing risk factors like sm...

Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes.

Scientific reports
Malnutrition is a multidomain problem affecting 54% of older adults in long-term care (LTC). Monitoring nutritional intake in LTC is laborious and subjective, limiting clinical inference capabilities. Recent advances in automatic image-based food est...

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Computational and mathematical methods in medicine
Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health cris...

A deep learning framework with an embedded-based feature selection approach for the early detection of the Alzheimer's disease.

Computers in biology and medicine
Ageing is associated with various ailments including Alzheimer 's disease (AD), which is a progressive form of dementia. AD symptoms develop over a period of years and, unfortunately, there is no cure. Existing AD treatments can only slow down the pr...